Release: 1.4.46 | Release Date: January 3, 2023

# SQLAlchemy 1.4 Documentation

# Base Type API

Object Name | Description
--- | ---
Concatenable | A mixin that marks a type as supporting ‘concatenation’, typically strings.
ExternalType | mixin that defines attributes and behaviors specific to third-party datatypes.
Indexable | A mixin that marks a type as supporting indexing operations, such as array or JSON structures.
NullType | An unknown type.
TypeEngine | The ultimate base class for all SQL datatypes.
Variant | A wrapping type that selects among a variety of implementations based on dialect in use.

class sqlalchemy.types.TypeEngine

  The ultimate base class for all SQL datatypes.

  Common subclasses of `TypeEngine` include `String`, `Integer`, and `Boolean`.

  For an overview of the SQLAlchemy typing system, see SQL Datatype Objects.

  See also

  SQL Datatype Objects

  Members

  operate(), reverse_operate(), adapt(), as_generic(), bind_expression(), bind_processor(), coerce_compared_value(), column_expression(), comparator_factory, compare_against_backend(), compare_values(), compile(), dialect_impl(), evaluates_none(), get_dbapi_type(), hashable, literal_processor(), python_type, result_processor(), should_evaluate_none, sort_key_function, with_variant()

  Class signature

  class `sqlalchemy.types.TypeEngine` (`sqlalchemy.sql.visitors.Traversible`)

  class Comparator(expr)

    Base class for custom comparison operations defined at the type level. See `TypeEngine.comparator_factory`.

    Class signature

    class `sqlalchemy.types.TypeEngine.Comparator` (`sqlalchemy.sql.expression.ColumnOperators`)

    method `sqlalchemy.types.TypeEngine.Comparator.`operate(op, *other, **kwargs)

      Operate on an argument.

      This is the lowest level of operation, raises `NotImplementedError` by default.

      Overriding this on a subclass can allow common behavior to be applied to all operations. For example, overriding `ColumnOperators` to apply `func.lower()` to the left and right side:

          class MyComparator(ColumnOperators):
              def operate(self, op, other, **kwargs):
                  return op(func.lower(self), func.lower(other), **kwargs)

      Parameters:

        - op – Operator callable.

        - *other – the ‘other’ side of the operation. Will be a single scalar for most operations.

        - **kwargs – modifiers. These may be passed by special operators such as `ColumnOperators.contains()`.

    method `sqlalchemy.types.TypeEngine.Comparator.`reverse_operate(op, other, **kwargs)

      Reverse operate on an argument.

      Usage is the same as `operate()`.

  method `sqlalchemy.types.TypeEngine.`adapt(cls, **kw)

    Produce an “adapted” form of this type, given an “impl” class to work with.

    This method is used internally to associate generic types with “implementation” types that are specific to a particular dialect.

  method `sqlalchemy.types.TypeEngine.`as_generic(allow_nulltype=False)

    Return an instance of the generic type corresponding to this type using heuristic rule. The method may be overridden if this heuristic rule is not sufficient.

        >>> from sqlalchemy.dialects.mysql import INTEGER
        >>> INTEGER(display_width=4).as_generic()
        Integer()

        >>> from sqlalchemy.dialects.mysql import NVARCHAR
        >>> NVARCHAR(length=100).as_generic()
        Unicode(length=100)

    New in version 1.4.0b2.

    See also

    Reflecting with Database-Agnostic Types - describes the use of `TypeEngine.as_generic()` in conjunction with the `DDLEvents.column_reflect()` event, which is its intended use.

  method `sqlalchemy.types.TypeEngine.`bind_expression(bindvalue)

    Given a bind value (i.e. a `BindParameter` instance), return a SQL expression in its place.

    This is typically a SQL function that wraps the existing bound parameter within the statement. It is used for special data types that require literals being wrapped in some special database function in order to coerce an application-level value into a database-specific format. It is the SQL analogue of the `TypeEngine.bind_processor()` method.

    This method is called during the SQL compilation phase of a statement, when rendering a SQL string. It is not called against specific values.

    Note that this method, when implemented, should always return the exact same structure, without any conditional logic, as it may be used in an executemany() call against an arbitrary number of bound parameter sets.

    Note

    This method is only called relative to a dialect specific type object, which is often private to a dialect in use and is not the same type object as the public facing one, which means it’s not feasible to subclass a `TypeEngine` class in order to provide an alternate `TypeEngine.bind_expression()` method, unless subclassing the `UserDefinedType` class explicitly.

    To provide alternate behavior for `TypeEngine.bind_expression()`, implement a `TypeDecorator` class and provide an implementation of `TypeDecorator.bind_expression()`.

    See also

    Augmenting Existing Types

    See also

    Applying SQL-level Bind/Result Processing

  method `sqlalchemy.types.TypeEngine.`bind_processor(dialect)

    Return a conversion function for processing bind values.

    Returns a callable which will receive a bind parameter value as the sole positional argument and will return a value to send to the DB-API.

    If processing is not necessary, the method should return `None`.

    Note

    This method is only called relative to a dialect specific type object, which is often private to a dialect in use and is not the same type object as the public facing one, which means it’s not feasible to subclass a `TypeEngine` class in order to provide an alternate `TypeEngine.bind_processor()` method, unless subclassing the `UserDefinedType` class explicitly.

    To provide alternate behavior for `TypeEngine.bind_processor()`, implement a `TypeDecorator` class and provide an implementation of `TypeDecorator.process_bind_param()`.

    See also

    Augmenting Existing Types

    Parameters:

      dialect – Dialect instance in use.

  method `sqlalchemy.types.TypeEngine.`coerce_compared_value(op, value)

    Suggest a type for a ‘coerced’ Python value in an expression.

    Given an operator and value, gives the type a chance to return a type which the value should be coerced into.

    The default behavior here is conservative; if the right-hand side is already coerced into a SQL type based on its Python type, it is usually left alone.

    End-user functionality extension here should generally be via `TypeDecorator`, which provides more liberal behavior in that it defaults to coercing the other side of the expression into this type, thus applying special Python conversions above and beyond those needed by the DBAPI to both ides. It also provides the public method `TypeDecorator.coerce_compared_value()` which is intended for end-user customization of this behavior.

  method `sqlalchemy.types.TypeEngine.`column_expression(colexpr)

    Given a SELECT column expression, return a wrapping SQL expression.

    This is typically a SQL function that wraps a column expression as rendered in the columns clause of a SELECT statement. It is used for special data types that require columns to be wrapped in some special database function in order to coerce the value before being sent back to the application. It is the SQL analogue of the `TypeEngine.result_processor()` method.

    This method is called during the SQL compilation phase of a statement, when rendering a SQL string. It is not called against specific values.

    Note

    This method is only called relative to a dialect specific type object, which is often private to a dialect in use and is not the same type object as the public facing one, which means it’s not feasible to subclass a `TypeEngine` class in order to provide an alternate `TypeEngine.column_expression()` method, unless subclassing the `UserDefinedType` class explicitly.

    To provide alternate behavior for `TypeEngine.column_expression()`, implement a `TypeDecorator` class and provide an implementation of `TypeDecorator.column_expression()`.

    See also

    Augmenting Existing Types

    See also

    Applying SQL-level Bind/Result Processing

  attribute `sqlalchemy.types.TypeEngine.`comparator_factory

    alias of `Comparator`

  method `sqlalchemy.types.TypeEngine.`compare_against_backend(dialect, conn_type)

    Compare this type against the given backend type.

    This function is currently not implemented for SQLAlchemy types, and for all built in types will return `None`. However, it can be implemented by a user-defined type where it can be consumed by schema comparison tools such as Alembic autogenerate.

    A future release of SQLAlchemy will potentially implement this method for builtin types as well.

    The function should return True if this type is equivalent to the given type; the type is typically reflected from the database so should be database specific. The dialect in use is also passed. It can also return False to assert that the type is not equivalent.

    Parameters:

      - dialect – a `Dialect` that is involved in the comparison.

      - conn_type – the type object reflected from the backend.

    New in version 1.0.3.

  method `sqlalchemy.types.TypeEngine.`compare_values(x, y)

    Compare two values for equality.

  method `sqlalchemy.types.TypeEngine.`compile(dialect=None)

    Produce a string-compiled form of this `TypeEngine`.

    When called with no arguments, uses a “default” dialect to produce a string result.

    Parameters:

      dialect – a `Dialect` instance.

  method `sqlalchemy.types.TypeEngine.`dialect_impl(dialect)

    Return a dialect-specific implementation for this `TypeEngine`.

  method `sqlalchemy.types.TypeEngine.`evaluates_none()

    Return a copy of this type which has the `should_evaluate_none` flag set to True.

    E.g.:

        Table(
            'some_table', metadata,
            Column(
                String(50).evaluates_none(),
                nullable=True,
                server_default='no value')
        )

    The ORM uses this flag to indicate that a positive value of `None` is passed to the column in an INSERT statement, rather than omitting the column from the INSERT statement which has the effect of firing off column-level defaults. It also allows for types which have special behavior associated with the Python None value to indicate that the value doesn’t necessarily translate into SQL NULL; a prime example of this is a JSON type which may wish to persist the JSON value `'null'`.

    In all cases, the actual NULL SQL value can be always be persisted in any column by using the `null` SQL construct in an INSERT statement or associated with an ORM-mapped attribute.

    Note

    The “evaluates none” flag does not apply to a value of `None` passed to `Column.default` or `Column.server_default`; in these cases, `None` still means “no default”.

    New in version 1.1.

    See also

    Forcing NULL on a column with a default - in the ORM documentation

    `JSON.none_as_null` - PostgreSQL JSON interaction with this flag.

    `TypeEngine.should_evaluate_none` - class-level flag

  method `sqlalchemy.types.TypeEngine.`get_dbapi_type(dbapi)

    Return the corresponding type object from the underlying DB-API, if any.

    This can be useful for calling `setinputsizes()`, for example.

  attribute `sqlalchemy.types.TypeEngine.`hashable = True

    Flag, if False, means values from this type aren’t hashable.

    Used by the ORM when uniquing result lists.

  method `sqlalchemy.types.TypeEngine.`literal_processor(dialect)

    Return a conversion function for processing literal values that are to be rendered directly without using binds.

    This function is used when the compiler makes use of the “literal_binds” flag, typically used in DDL generation as well as in certain scenarios where backends don’t accept bound parameters.

    Returns a callable which will receive a literal Python value as the sole positional argument and will return a string representation to be rendered in a SQL statement.

    Note

    This method is only called relative to a dialect specific type object, which is often private to a dialect in use and is not the same type object as the public facing one, which means it’s not feasible to subclass a `TypeEngine` class in order to provide an alternate `TypeEngine.literal_processor()` method, unless subclassing the `UserDefinedType` class explicitly.

    To provide alternate behavior for `TypeEngine.literal_processor()`, implement a `TypeDecorator` class and provide an implementation of `TypeDecorator.process_literal_param()`.

    See also

    Augmenting Existing Types

  attribute `sqlalchemy.types.TypeEngine.`python_type

    Return the Python type object expected to be returned by instances of this type, if known.

    Basically, for those types which enforce a return type, or are known across the board to do such for all common DBAPIs (like `int` for example), will return that type.

    If a return type is not defined, raises `NotImplementedError`.

    Note that any type also accommodates NULL in SQL which means you can also get back `None` from any type in practice.

  method `sqlalchemy.types.TypeEngine.`result_processor(dialect, coltype)

    Return a conversion function for processing result row values.

    Returns a callable which will receive a result row column value as the sole positional argument and will return a value to return to the user.

    If processing is not necessary, the method should return `None`.

    Note

    This method is only called relative to a dialect specific type object, which is often private to a dialect in use and is not the same type object as the public facing one, which means it’s not feasible to subclass a `TypeEngine` class in order to provide an alternate `TypeEngine.result_processor()` method, unless subclassing the `UserDefinedType` class explicitly.

    To provide alternate behavior for `TypeEngine.result_processor()`, implement a `TypeDecorator` class and provide an implementation of `TypeDecorator.process_result_value()`.

    See also

    Augmenting Existing Types

    Parameters:

      - dialect – Dialect instance in use.

      - coltype – DBAPI coltype argument received in cursor.description.

  attribute `sqlalchemy.types.TypeEngine.`should_evaluate_none = False

    If True, the Python constant `None` is considered to be handled explicitly by this type.

    The ORM uses this flag to indicate that a positive value of `None` is passed to the column in an INSERT statement, rather than omitting the column from the INSERT statement which has the effect of firing off column-level defaults. It also allows types which have special behavior for Python None, such as a JSON type, to indicate that they’d like to handle the None value explicitly.

    To set this flag on an existing type, use the `TypeEngine.evaluates_none()` method.

    See also

    `TypeEngine.evaluates_none()`

    New in version 1.1.

  attribute `sqlalchemy.types.TypeEngine.`sort_key_function = None

    A sorting function that can be passed as the key to sorted.

    The default value of `None` indicates that the values stored by this type are self-sorting.

    New in version 1.3.8.

  method `sqlalchemy.types.TypeEngine.`with_variant(type_, dialect_name)

    Produce a new type object that will utilize the given type when applied to the dialect of the given name.

    e.g.:

        from sqlalchemy.types import String
        from sqlalchemy.dialects import mysql

        s = String()

        s = s.with_variant(mysql.VARCHAR(collation='foo'), 'mysql')

    The construction of `TypeEngine.with_variant()` is always from the “fallback” type to that which is dialect specific. The returned type is an instance of `Variant`, which itself provides a `Variant.with_variant()` that can be called repeatedly.

    Parameters:

      - type_ – a `TypeEngine` that will be selected as a variant from the originating type, when a dialect of the given name is in use.

      - dialect_name – base name of the dialect which uses this type. (i.e. `'postgresql'`, `'mysql'`, etc.)

    See also

    Using “UPPERCASE” and Backend-specific types for multiple backends - illustrates the use of `TypeEngine.with_variant()`.

class sqlalchemy.types.Concatenable

  Members

  comparator_factory

  A mixin that marks a type as supporting ‘concatenation’, typically strings.

  class Comparator(expr)

    Class signature

    class `sqlalchemy.types.Concatenable.Comparator` (`sqlalchemy.types.Comparator`)

  attribute `sqlalchemy.types.Concatenable.`comparator_factory

    alias of `Comparator`

class sqlalchemy.types.Indexable

  A mixin that marks a type as supporting indexing operations, such as array or JSON structures.

  Members

  comparator_factory

  New in version 1.1.0.

  class Comparator(expr)

    Class signature

    class `sqlalchemy.types.Indexable.Comparator` (`sqlalchemy.types.Comparator`)

  attribute `sqlalchemy.types.Indexable.`comparator_factory

    alias of `Comparator`

class sqlalchemy.types.NullType

  An unknown type.

  `NullType` is used as a default type for those cases where a type cannot be determined, including:

  - During table reflection, when the type of a column is not recognized by the `Dialect`

  - When constructing SQL expressions using plain Python objects of unknown types (e.g. `somecolumn == my_special_object`)

  - When a new `Column` is created, and the given type is passed as `None` or is not passed at all.

  The `NullType` can be used within SQL expression invocation without issue, it just has no behavior either at the expression construction level or at the bind-parameter/result processing level. `NullType` will result in a `CompileError` if the compiler is asked to render the type itself, such as if it is used in a `cast()` operation or within a schema creation operation such as that invoked by `MetaData.create_all()` or the `CreateTable` construct.

  Class signature

  class `sqlalchemy.types.NullType` (`sqlalchemy.types.TypeEngine`)

class sqlalchemy.types.ExternalType

  mixin that defines attributes and behaviors specific to third-party datatypes.

  “Third party” refers to datatypes that are defined outside the scope of SQLAlchemy within either end-user application code or within external extensions to SQLAlchemy.

  Subclasses currently include `TypeDecorator` and `UserDefinedType`.

  Members

  cache_ok

  New in version 1.4.28.

  attribute `sqlalchemy.types.ExternalType.`cache_ok = None

    Indicate if statements using this `ExternalType` are “safe to cache”.

    The default value `None` will emit a warning and then not allow caching of a statement which includes this type. Set to `False` to disable statements using this type from being cached at all without a warning. When set to `True`, the object’s class and selected elements from its state will be used as part of the cache key. For example, using a `TypeDecorator`:

        class MyType(TypeDecorator):
            impl = String

            cache_ok = True

            def __init__(self, choices):
                self.choices = tuple(choices)
                self.internal_only = True

    The cache key for the above type would be equivalent to:

        >>> MyType(["a", "b", "c"])._static_cache_key
        (<class '__main__.MyType'>, ('choices', ('a', 'b', 'c')))

    The caching scheme will extract attributes from the type that correspond to the names of parameters in the `__init__()` method. Above, the “choices” attribute becomes part of the cache key but “internal_only” does not, because there is no parameter named “internal_only”.

    The requirements for cacheable elements is that they are hashable and also that they indicate the same SQL rendered for expressions using this type every time for a given cache value.

    To accommodate for datatypes that refer to unhashable structures such as dictionaries, sets and lists, these objects can be made “cacheable” by assigning hashable structures to the attributes whose names correspond with the names of the arguments. For example, a datatype which accepts a dictionary of lookup values may publish this as a sorted series of tuples. Given a previously un-cacheable type as:

        class LookupType(UserDefinedType):
            '''a custom type that accepts a dictionary as a parameter.

            this is the non-cacheable version, as "self.lookup" is not
            hashable.

            '''

            def __init__(self, lookup):
                self.lookup = lookup

            def get_col_spec(self, **kw):
                return "VARCHAR(255)"

            def bind_processor(self, dialect):
                # ...  works with "self.lookup" ...

    Where “lookup” is a dictionary. The type will not be able to generate a cache key:

        >>> type_ = LookupType({"a": 10, "b": 20})
        >>> type_._static_cache_key
        <stdin>:1: SAWarning: UserDefinedType LookupType({'a': 10, 'b': 20}) will not
        produce a cache key because the ``cache_ok`` flag is not set to True.
        Set this flag to True if this type object's state is safe to use
        in a cache key, or False to disable this warning.
        symbol('no_cache')

    If we did set up such a cache key, it wouldn’t be usable. We would get a tuple structure that contains a dictionary inside of it, which cannot itself be used as a key in a “cache dictionary” such as SQLAlchemy’s statement cache, since Python dictionaries aren’t hashable:

        >>> # set cache_ok = True
        >>> type_.cache_ok = True

        >>> # this is the cache key it would generate
        >>> key = type_._static_cache_key
        >>> key
        (<class '__main__.LookupType'>, ('lookup', {'a': 10, 'b': 20}))

        >>> # however this key is not hashable, will fail when used with
        >>> # SQLAlchemy statement cache
        >>> some_cache = {key: "some sql value"}
        Traceback (most recent call last): File "<stdin>", line 1,
        in <module> TypeError: unhashable type: 'dict'

    The type may be made cacheable by assigning a sorted tuple of tuples to the “.lookup” attribute:

        class LookupType(UserDefinedType):
            '''a custom type that accepts a dictionary as a parameter.

            The dictionary is stored both as itself in a private variable,
            and published in a public variable as a sorted tuple of tuples,
            which is hashable and will also return the same value for any
            two equivalent dictionaries.  Note it assumes the keys and
            values of the dictionary are themselves hashable.

            '''

            cache_ok = True

            def __init__(self, lookup):
                self._lookup = lookup

                # assume keys/values of "lookup" are hashable; otherwise
                # they would also need to be converted in some way here
                self.lookup = tuple(
                    (key, lookup[key]) for key in sorted(lookup)
                )

            def get_col_spec(self, **kw):
                return "VARCHAR(255)"

            def bind_processor(self, dialect):
                # ...  works with "self._lookup" ...

    Where above, the cache key for `LookupType({"a": 10, "b": 20})` will be:

        >>> LookupType({"a": 10, "b": 20})._static_cache_key
        (<class '__main__.LookupType'>, ('lookup', (('a', 10), ('b', 20))))

    New in version 1.4.14: - added the `cache_ok` flag to allow some configurability of caching for `TypeDecorator` classes.

    New in version 1.4.28: - added the `ExternalType` mixin which generalizes the `cache_ok` flag to both the `TypeDecorator` and `UserDefinedType` classes.

    See also

    SQL Compilation Caching

class sqlalchemy.types.Variant(base, mapping)

  A wrapping type that selects among a variety of implementations based on dialect in use.

  The `Variant` type is typically constructed using the `TypeEngine.with_variant()` method.

  See also

  `TypeEngine.with_variant()` for an example of use.

  Members

  __init__(), with_variant()

  Class signature

  class `sqlalchemy.types.Variant` (`sqlalchemy.types.TypeDecorator`)

  method `sqlalchemy.types.Variant.`__init__(base, mapping)

    Construct a new `Variant`.

    Parameters:

      - base – the base ‘fallback’ type

      - mapping – dictionary of string dialect names to `TypeEngine` instances.

  method `sqlalchemy.types.Variant.`with_variant(type_, dialect_name)

    Return a new `Variant` which adds the given type + dialect name to the mapping, in addition to the mapping present in this `Variant`.

    Parameters:

      - type_ – a `TypeEngine` that will be selected as a variant from the originating type, when a dialect of the given name is in use.

      - dialect_name – base name of the dialect which uses this type. (i.e. `'postgresql'`, `'mysql'`, etc.)